ML Software/Data Engineer Music Creation Apps
Imagine what you could do here. At Apple, new ideas have a way of becoming
great products very quickly. Bring passion and dedication to your job and there's
no telling what you could accomplish.
The Music Creation Apps team (Logic Pro, GarageBand, MainStage) is looking for
a talented Software/Data Engineer to help build the next generation of AI-driven
features for our apps. Our highly cross-functional team works closely with
Engineering, Product Design and QA, as well as other audio experts across Apple,
to develop advanced machine learning AI algorithms, augment the music-making
process and provide artists help right when they need it — all while ensuring they
maintain full creative control.
Make a difference. You are a motivated self-starter, comfortable navigating through
ambiguity to create the next generation of AI-driven music making experiences
across Apple’s Music Creation Apps.
Your responsibilities will include building and maintaining audio data sets, driving
data engineering solutions to collect, annotate and augment musical data,
designing tools and visualisations for data analysis, and support building and
evaluating cutting-edge machine learning models for music analysis and
processing.
We are looking for a strong engineer who also has a keen sense of
how to build good products. Your curiosity drives you to explore new technologies
and apply creative solutions to problems. The ideal candidate pays close attention
to details, but also keeps sight of the bigger picture.
- BS/MS in Computer Science, Data Engineering, Machine Learning, or other
- related discipline or equivalent professional experience in software/data
- engineering.
- Strong software development skills with Python, C++ or Swift.
- Experience in developing audio manipulation and processing pipelines.
- Expertise in data quality evaluation and developing visualisations and tooling.
- Fluent in English.
- Experience with cloud computing platforms (e.g., AWS, GCP).
- Experience in managing and maintaining large datasets and working with
- complex audio or musical data.
- Familiar with developing machine learning models for audio analysis or
- processing.
- Familiar with version control systems such as Git.
- Passion for music and audio technologies, recording or producing music or
- playing an instrument is a big plus.